Get Ready with AIF Exam Dumps (2023)
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NEW QUESTION # 21
An agent based model is a simul-ation of autonomous agents (individual and collective). What can be used to learn from the data generated by the simul-ations?
- A. Machine Learning.
- B. A spreadsheet
- C. Python.
- D. Paraview.
Answer: B
Explanation:
https://www.pnas.org/doi/10.1073/pnas.082080899
NEW QUESTION # 22
What function is used in a Neural Network?
- A. Trigonometric.
- B. Activation.
- C. Linear.
- D. Statistical.
Answer: B
Explanation:
Explanation
Activation Functions
An activation function in a neural network defines how the weighted sum of the input is transformed into an
output from a node or nodes in a layer of the network.
https://machinelearningmastery.com/choose-an-activation-function-for-deep-learning/#:~:text=An%20activation
NEW QUESTION # 23
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Over-fitting
- B. Boosting.
- C. Activation.
- D. Iteration.
Answer: B
Explanation:
Explanation
* Weak Learner: Colloquially, a model that performs slightly better than a naive model.
More formally, the notion has been generalized to multi-class classification and has a different meaning beyond better than 50 percent accuracy.
For binary classification, it is wellknown that the exact requirement for weak learners is to be better than random guess. [...] Notice that requiring base learners to be better than random guess is too weak for multi-class problems, yet requiring better than 50% accuracy is too stringent.
- Page 46, Ensemble Methods, 2012.
It is based on formal computational learning theory that proposes a class of learning methods that possess weakly learnability, meaning that they perform better than random guessing. Weak learnability is proposed as a simplification of the more desirable strong learnability, where a learnable achieved arbitrary good classification accuracy.
A weaker model of learnability, called weak learnability, drops the requirement that the learner be able to achieve arbitrarily high accuracy; a weak learning algorithm needs only output an hypothesis that performs slightly better (by an inverse polynomial) than random guessing.
- The Strength of Weak Learnability, 1990.
It is a useful concept as it is often used to describe the capabilities of contributing members of ensemble learning algorithms. For example, sometimes members of a bootstrap aggregation are referred to as weak learners as opposed to strong, at least in the colloquial meaning of the term.
More specifically, weak learners are the basis for the boosting class of ensemble learning algorithms.
The term boosting refers to a family of algorithms that are able to convert weak learners to strong learners.
https://machinelearningmastery.com/strong-learners-vs-weak-learners-for-ensemble-learning/ The best technique to adopt when a weak learner's hypothesis accuracy is only slightly better than 50% is boosting. Boosting is an ensemble learning technique that combines multiple weak learners (i.e., models with a low accuracy) to create a more powerful model. Boosting works by iteratively learning a series of weak learners, each of which is slightly better than random guessing. The output of each weak learner is then combined to form a more accurate model. Boosting is a powerful technique that has been proven to improve the accuracy of a wide range of machine learning tasks. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.
NEW QUESTION # 24
In an Al project the domain expert is the person...
- A. who measures the trustworthiness of the Al system
- B. with special knowledge or skills in the area of endeavour and defines what is fit for purpose'
- C. whomanages the agile project and writes the technical terms of reference
- D. with technical and managerial oversight of the business plan
Answer: A
NEW QUESTION # 25
In Machine learning what are a brain's axons called?
- A. Tetrahedra.
- B. Nodes
- C. Dendrites
- D. Edges
Answer: B
Explanation:
Explanation
In Machine Learning, the brain's axons are referred to as nodes. Nodes are the components of a neural network that are responsible for processing the input data and generating the output. A node is a mathematical function that takes input data, performs a computation on it, and produces an output. Each node is connected to other nodes in the network via edges, which represent the strength of the connection between the respective nodes. The strength of the connection between two nodes is determined by the weights assigned to each edge.
The weights are adjusted during the training process to generate the desired results.
For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf) or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).
NEW QUESTION # 26
What is an intelligent robot?
- A. A robot that acts like ahuman.
- B. A robot that has consciousness
- C. A robot that takes the place of a human.
- D. A robot that uses Al techniques.
Answer: D
Explanation:
Explanation
An intelligent robot is one that uses AI techniques, such as machine learning and natural language processing, to perceive, plan and act on its environment. Intelligent robots are able to process large amounts of data quickly and accurately, allowing them to make decisions and carry out tasks autonomously. Intelligent robots can be used in a variety of applications, from industrial automation to healthcare.
NEW QUESTION # 27
In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference.
(Select the missing word.)
- A. The central limit
- B. Boltzmann's
- C. Bayes'
- D. Kolmogorov's
Answer: D
NEW QUESTION # 28
An Al agent relies on its perceptual input. This is called the agent's what?
- A. World
- B. Environment
- C. Position
- D. Percept
Answer: D
Explanation:
Explanation
* Performance Measure of Agent It is the criteria, which determines how successful an agent is.
* Behavior of Agent It is theaction that agent performs after any given sequence of percepts.
* Percept It is agent's perceptual inputs at a given instance.
* Percept Sequence It is the history of all that an agent has perceived till date.
* Agent Function It is a map from the preceptsequence to an action.
Agent Terminology
https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_agents_and_environments.htm An AI agent relies on its perceptual input, which is referred to as the agent's percept. This is the data that the agent collects through its sensors about its environment. The percept allows the agent to make decisions and take actions based on its environment. The agent's percept is important for Artificial Intelligence systems to be able to operate effectively. References:
[1] BCS Foundation Certificate In Artificial Intelligence Study Guide, "Reinforcement Learning", p.96-97. [2] APMG-International.com, "Foundations of Artificial Intelligence" [3] EXIN.com, "Foundations of Artificial Intelligence"
NEW QUESTION # 29
Sustainability focuses on which three core areas?
- A. Social, Economic and Entrepreneurial.
- B. Scientific, Environmental and Economic.
- C. Social, Economic and Environmental.
- D. Social, Entrepreneurial and Environmental.
Answer: C
Explanation:
The term sustainability is broadly used to indicate programs, initiatives and actions aimed at the preservation of a particular resource. However, it actually refers to four distinct areas: human, social, economic and environmental - known as the four pillars of sustainability.
https://www.futurelearn.com/info/courses/sustainable-business/0/steps/78337#:~:text=However%2C%20it%20actually%20refers%20to,the%20four%20pillars%20of%20sustainability.&text=Human%20sustainability%20aims%20to%20maintain%20and%20improve%20the%20human%20capital%20in%20society.
NEW QUESTION # 30
In Machine learning what are a brain's axons called?
- A. Tetrahedra.
- B. Dendrites
- C. Nodes
- D. Edges
Answer: B
NEW QUESTION # 31
What is one of the MAIN contributions of Al to the rapid development of The Fourth Industrial Revolution?
- A. Big Data
- B. Automation
- C. Al personal assistants.
- D. Enhanced design.
Answer: A
Explanation:
https://research.com/careers/what-is-the-fourth-industrial-revolution
NEW QUESTION # 32
What term do computer scientists and economists use to describe how happy an agent is?
- A. Index.
- B. Return
- C. Utility.
- D. Warm.
Answer: C
Explanation:
https://griffinshare.fontbonne.edu/cgi/viewcontent.cgi?article=1008&context=ijds
NEW QUESTION # 33
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?
- A. Batch learning.
- B. Online learning.
- C. Patchwork learning.
- D. Big Data learning.
Answer: B
Explanation:
Explanation
Online learning is a type of machine learning that can be used when a large dataset is limited in computational resources or if the data is frequently changing. It allows the system to learn from new data as it is being presented, rather than having to re-train the entire dataset each time new data is added. This makes it more efficient and effective than batch learning, as it only needs to process the new data and not the entire dataset.
Online learning is often used in applications such as fraud detection, where new data is constantly being added and needs to be analyzed quickly.
For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf) or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).
NEW QUESTION # 34
What function is used in a Neural Network?
- A. Trigonometric.
- B. Activation.
- C. Linear.
- D. Statistical.
Answer: B
Explanation:
Activation Functions
An activation function in a neural network defines how the weighted sum of the input is transformed into an output from a node or nodes in a layer of the network.
https://machinelearningmastery.com/choose-an-activation-function-for-deep-learning/#:~:text=An%20activation%20function%20in%20a,a%20layer%20of%20the%20network.
NEW QUESTION # 35
Healthcare can benefit from Al, and in particular Machine Learning, an example of which is?
- A. Automated blood sampling.
- B. Diagnostic image analysis
- C. Autonomous vehicles.
- D. Autonomous wheelchairs.
Answer: B
NEW QUESTION # 36
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Human plus machine.
- B. Human.
- C. Machine.
- D. Artificial General Intelligence.
Answer: C
NEW QUESTION # 37
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